26 to 50 of 672 Machine Learning Jobs in London

intersection of machine learning, computational science , and emerging hybrid computing architectures . The work focuses on algorithmic innovation , generative modelling , and benchmarking ML systems on cutting‑edge hardware platforms. You will contribute to the development of new machine learning algorithms designed for advanced computing systems that … extend beyond traditional GPU/TPU environments. The role involves close collaboration with researchers across ML, physics, and scientific computing, with a strong emphasis on generative models , numerical methods , and hybrid quantum‑classical approaches . Essential Experience Experience with heterogeneous computing hardware (HPC, NPUs, ASICs, quantum systems). Strong background ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

Senior Machine Learning/AI Engineer £100,000-£125,000 Hybrid working model: three days per week in the office (Monday, Tuesday, plus one flexible day) LDN 27 days of annual leave plus 8 bank holidays and 5 additional days, including life event, volunteering, and company-wide wellbeing … emerging AI tools and techniques, applying them to deliver exceptional, user-focused experiences. What the Company Is Looking For Hands-On AI/ML Expertise: Experience building and deploying machine learning models using frameworks such as PyTorch, TensorFlow, or scikit-learn. LLM Experience: Proven experience working with large ...

applied artificial intelligence, solving complex real-world problems in national security and defence environments. The Role You will design, develop and deploy advanced ML models within secure environments, contributing across the full lifecycle from research through to production. Projects may include: Computer vision and pattern recognition systems Synthetic data generation … modelling Deep neural networks (DNNs) for real-world defence applications Simulation and AI-driven modelling environments Advanced research-led ML solutions You will collaborate with research scientists, software engineers and domain experts to translate cutting-edge techniques into deployable capability. Key Skills & Experience Proven experience working within the UK defence ...

Main office in London but have a further 6 worldwide. Work with some of the largest FinTech companies globally. Looking to utilise AI/ML to simplify their processes and products. Award winning business and part of a wider wealth-management group. The Role – Head of Machine Learning … week in the office. Lead a small team of Data Scientists. Mostly technical but small amount of people management. Lead the integration of ML/AI across the company’s core SaaS products. Work with clients & multiple teams to ensure AI solutions are implemented smoothly. Brand new role which offers ...

combines scale, innovation and purpose. As a Machine Learning Engineer, you'll help maintain the stability and performance of core data and ML systems across Europe. This technical engineering role focuses on reliability, optimisation and critical fixes, ideal if you excel at investigating and debugging complex data flows … ML issues in live production environments. We're looking for individuals with: Experience: Proven background as a Machine Learning Engineer. Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex ...

Learning Engineer to join our growing team. This is an exciting opportunity for women who want to advance their career in AI/ML, work on meaningful projects, and thrive in a supportive, collaborative environment. What Youll Do: Design, develop, and deploy machine learning models using modern … stakeholders to turn ideas into impactful solutions. Optimize and deploy models with tools like TensorFlow Serving, TorchServe, ONNX, and TensorRT. Build and manage ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines. Work with large-scale data using PySpark and integrate ML solutions into production environments. Monitor and improve model ...

ingestion Marketplace or data aggregation platforms Entity resolution, record linkage or deduplication systems Matching systems or recommendation engines Geospatial or address based data platforms ML systems deployed into production You do not need sector experience, but you should be comfortable working with complex datasets where the same entity appears across … multiple sources. What They Are Looking For Strong Data Science background with hands on machine learning experience Experience deploying ML models into production environments Understanding of data engineering concepts and modern cloud data platforms Architectural thinking around data platforms and ML systems Experience working with messy, multi source ...

data is enriched, automated, and delivered across multi-tenant environments. Theyre now hiring a Machine Learning Engineerto help build intelligent, production-grade ML systems at the core of their platform. Responsibilities Build and deploy machine learning models into production. Develop ML systems optimised for a multi … SaaS platform. Create ETL pipelines for large, complex property datasets. Monitor, tune, and iterate on model performance. Collaborate with product and engineering teams on ML-driven features. Document solutions and communicate clearly with technical and non-technical stakeholders. Key Skills 4+ years as a Machine Learning Engineer ...

combines scale, innovation and purpose. As a Machine Learning Engineer, you'll help maintain the stability and performance of core data and ML systems across Europe. This technical engineering role focuses on reliability, optimisation and critical fixes, ideal if you excel at investigating and debugging complex data flows … ML issues in live production environments. We're looking for individuals with: Experience: Proven background as a Machine Learning Engineer. Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation: experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex ...

Data scientist- Principal Data Scientist/Senior Machine Learning Scientist/AI/ML Solution Architect Key Responsibilities Lead end-to-end machine learning solution delivery for complex enterprise use cases Translate ambiguous business challenges into structured ML problem statements and solution architectures Design, develop … engineering teams to transition models into scalable production systems Mentor data scientists and uphold modelling standards, documentation, and reproducibility best practices Contribute to reusable ML frameworks, accelerators, and innovation initiatives Required Experience & Qualifications 15+ years of total professional experience , including 8+ years of hands-on experience in machine learning ...

machine learning models in production. Collaborating with data scientists, engineers, and stakeholders to integrate AI solutions into scalable products. Supporting the full ML lifecycle, from experimentation to deployment and optimisation. Applying best practices in data engineering and contributing to architectural decisions. Using modern MLOps tools and CI/… knowledge-sharing and continuous improvement. Technical Experience Were looking for experience in many of the following areas: Strong Python skills and familiarity with ML libraries such as Pandas, NumPy, and scikit-learn. Experience with frameworks such as TensorFlow, Keras, or PyTorch. Exposure to gradient boosting tools such as XGBoost, LightGBM ...

years’ commercial experience in Machine Learning Strong experience in Computer Vision (e.g. object detection, image classification, segmentation) Experience building, training and optimising ML models Python (NumPy, Pandas, scikit-learn) and frameworks such as TensorFlow or PyTorch Experience deploying models into production environments (cloud platforms, Docker, CI/… resided in the UK continuously for the last 5 years) These roles offer the opportunity to work on impactful, real-world projects where robust ML solutions are critical. If you’re exploring new contract opportunities and meet the above criteria, please apply or drop me a direct message. ...

solutions. Key Responsibilities: Design, build and deploy machine learning and AI solutions for enterprise clients Develop models using Python, PyTorch and modern ML frameworks Work with large datasets to train, evaluate and optimise models Implement and scale solutions on AWS (SageMaker, Bedrock, Lambda, etc.) Contribute to generative … Data Science roles Strong Python programming skills Hands-on experience with PyTorch Experience with Hugging Face transformers or similar frameworks Solid experience deploying ML solutions on AWS Understanding of MLOps, model deployment and performance optimisation Ability to work in a consultancy environment with multiple clients Desirable: Experience with LLMs ...

intersection of machine learning, product, and engineering, working closely with a world-class research team to turn advanced ML capabilities into a coherent, high-impact agent used on real-world problems. More specifically, you'll build the intelligence layer of their highly advanced agentic AI agent. … help design: The iterative interaction between the Agent and users The ML logic and decision workflows powering the Agent Reusable predictive pipelines that generalise across datasets Robust evaluation and model comparison frameworks This is a high-ownership role where you’ll shape core product architecture in a fast-moving environment. ...

Data Engineer - (Python, SQL, Machine Learning, AI, Cloud Storage) - Robotics/AI My global AI & Robotics client is looking for an experienced Data Engineer to join their data engineering team based in London. This is a data engineering role so you are expecting to have in-depth technical … knowledge of Python, SQL, Machine Learning, AI, Cloud Storage and managing large data sets. A commercial background or a demonstrable strong interest in robotics & AI is highly preferred for this role. Essential Skills Bachelor's or Master's degree in Data Science, Computer Science, or a related field. ...

efficient retrofit planning. Solutions in these areas will likely start by using heuristics and statistical methods with the opportunity and ambition to bring in machine learning over time. A successful candidate is a self-starter, passionate about applying their software skills to solve the urgent problem of building … processing services, ensuring high availability and performance across the platform. Ensuring the smooth delivery and deployment of new features and updates Design and implement machine learning models and algorithms to extract and sequence actionable insights from diverse data streams, including 2D imagery and 3D geometric data. Implement ...

commercial performance and competitive advantage. They are now seeking a Head of Data Science to define and lead the next phase of their ML capability. This is a strategic leadership role focused on building a scalable, high-impact data science function that consistently delivers measurable business outcomes. This … performance metrics, and positioning machine learning as a long-term strategic differentiator for the organisation. Skills & Experience Experience operating at scale where ML directly influences commercial performance A track record of building and leading high-performing data science teams Strong stakeholder management skills, with the ability to influence ...